update model card README.md

README.md

@@ -1,36 +1,12 @@
 ---
-language: 
-- ur
-
 license: apache-2.0
 tags:
-- automatic-speech-recognition
-- robust-speech-event
+- generated_from_trainer
 datasets:
-- mozilla-foundation/common_voice_8_0
-metrics:
-- wer
-- cer
+- common_voice
 model-index:
 - name: wav2vec2-large-xls-r-300m-Urdu
-  results:
-  - task: 
-      type: automatic-speech-recognition  # Required. Example: automatic-speech-recognition
-      name: Speech Recognition  # Optional. Example: Speech Recognition
-    dataset:
-      type: mozilla-foundation/common_voice_8_0  # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
-      name: Common Voice ur  # Required. Example: Common Voice zh-CN
-      args: ur         # Optional. Example: zh-CN
-    metrics:
-      - type: wer    # Required. Example: wer
-        value: 51.96 # Required. Example: 20.90
-        name: Test WER With LM    # Optional. Example: Test WER
-               # Optional. Example for BLEU: max_order
-      - type: cer    # Required. Example: wer
-        value: 22.69  # Required. Example: 20.90
-        name: Test CER    # Optional. Example: Test WER
-        
-
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -40,43 +16,48 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.5867
-- Wer: 0.6240
-- Cer: 0.2579
+- Loss: 0.9889
+- Wer: 0.5607
+- Cer: 0.2370
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
 
+More information needed
 
+## Training procedure
 
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 0.0003
-- train_batch_size: 16
+- learning_rate: 0.0001
+- train_batch_size: 32
 - eval_batch_size: 8
 - seed: 42
-- gradient_accumulation_steps: 4
+- gradient_accumulation_steps: 2
 - total_train_batch_size: 64
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- lr_scheduler_warmup_steps: 200
-- num_epochs: 100
-- mixed_precision_training: Native AMP
+- lr_scheduler_warmup_steps: 1000
+- num_epochs: 200
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
-|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
-| 11.1231       | 8.31  | 100  | 3.5275          | 1.0    | 1.0    |
-| 3.4028        | 16.63 | 200  | 3.1164          | 1.0    | 1.0    |
-| 3.1973        | 24.94 | 300  | 2.5590          | 1.0    | 1.0    |
-| 1.3774        | 33.31 | 400  | 1.4729          | 0.7646 | 0.3325 |
-| 0.5427        | 41.63 | 500  | 1.4140          | 0.6939 | 0.3001 |
-| 0.3541        | 49.94 | 600  | 1.4532          | 0.6580 | 0.2815 |
-| 0.26          | 58.31 | 700  | 1.5309          | 0.6403 | 0.2726 |
-| 0.2025        | 66.63 | 800  | 1.5230          | 0.6310 | 0.2655 |
-| 0.171         | 74.94 | 900  | 1.5578          | 0.6336 | 0.2632 |
-| 0.1511        | 83.31 | 1000 | 1.5733          | 0.6321 | 0.2635 |
-| 0.1352        | 91.63 | 1100 | 1.6022          | 0.6255 | 0.2608 |
-| 0.1192        | 99.94 | 1200 | 1.5867          | 0.6240 | 0.2579 |
+| Training Loss | Epoch  | Step | Validation Loss | Wer    | Cer    |
+|:-------------:|:------:|:----:|:---------------:|:------:|:------:|
+| 3.6398        | 30.77  | 400  | 3.3517          | 1.0    | 1.0    |
+| 2.9225        | 61.54  | 800  | 2.5123          | 1.0    | 0.8310 |
+| 1.2568        | 92.31  | 1200 | 0.9699          | 0.6273 | 0.2575 |
+| 0.8974        | 123.08 | 1600 | 0.9715          | 0.5888 | 0.2457 |
+| 0.7151        | 153.85 | 2000 | 0.9984          | 0.5588 | 0.2353 |
+| 0.6416        | 184.62 | 2400 | 0.9889          | 0.5607 | 0.2370 |
 
 
 ### Framework versions